Unified Scheduling for Predictable Communication Reliability in Industrial Cellular Networks
Unified Scheduling for Predictable Communication Reliability in Industrial Cellular Networks
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DOI:
10.1109/icii.2018.00022
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发表时间:
2018-10
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影响因子:
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通讯作者:
Yuwei Xie;Hongwei Zhang;Pengfei Ren
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文献类型:
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作者:
Yuwei Xie;Hongwei Zhang;Pengfei Ren
Cellular networks with D2D links are increasingly being explored for mission-critical applications, and it is critical to control interference among concurrent transmissions in a predictable manner to ensure the required communication reliability. To this end, we propose a Unified Cellular Scheduling (UCS) framework that, based on the Physical-Ratio-K (PRK) interference model, schedules uplink, downlink, and D2D transmissions in a unified manner to ensure predictable communication reliability while maximizing channel spatial reuse. UCS also provides a simple, effective approach to mode selection that maximizes the communication capacity for each involved communication pair. UCS effectively uses multiple channels for high throughput as well as resilience to channel fading and external interference. Leveraging the availability of base stations (BSes) as well as highspeed, out-of-band connectivity between BSes, UCS effectively orchestrates the functionalities of BSes and user equipment (UE) for light-weight control signaling and ease of incremental deployment and integration with existing cellular standards. We have implemented UCS using the open-source, standardscompliant cellular networking platform OpenAirInterface. We have validated the OpenAirInterface implementation using USRP B210 software-defined radios and lab deployment. We have also evaluated UCS through high-fidelity, at-scale simulation studies. Our experiments show that UCS ensures predictable communication reliability while achieving a higher channel spatial reuse rate than existing mechanisms. Additionally, the distributed UCS framework enables a channel spatial reuse rate statistically equal to that in the state-of-the-art centralized scheduling algorithm iOrder.